ABSTRACT Code lists are a key part of budget datasets as they serve for the coding of fiscal concepts within them. However, the great diversity of classifications across countries and concepts does not allow to presume upon their actual value, as dimension properties. In this paper we discuss the need for creating code lists Linked Data for the classifications used in fiscal datasets, in three basic steps. First, code lists have to be extracted from fiscal datasets, especially if there are no relevant metadata in the budget description, which could easily identify them. Next, code lists from different datasets or sources have to be represented in the same way, with SKOS vocabulary, thus they can be linked with each other. Finally, linking of similar code lists will also allow the linking of the containing datasets, increasing their data analysis and knowledge extraction possibilities
